RESEARCH ASSISTANTSHIP IN FOREST INVENTORY PLOT DESIGN Duke University is seeking candidates for a 1-year position as a Post-doctoral Researcher or Associate in Research with skills in remote sensing relating to forest inventory. The position is based in Newtown Square, PA with the USDA Forest Service, Northern Research Station (www.nrs.fs.fed.us/nimac/). The candidate will contribute to a research project in support of the US governments SilvaCarbon program (www.silvacarbon.org). The goal of the research project is to assess the effects of forest inventory plot design on both inventory efficiency and training data efficacy for remotely sensed image classification. This research will support the US governments commitment to contribute to scientific advances in the field of Measurement, Reporting and Verification (MRV) of carbon stocks as part of the United Nations REDD program.
Specific tasks will include: 1. Pre-processing GIS data in both raster and vector formats (including LiDAR datasets, Landsat and other high resolution imagery, shape file and other vector formats) 2. Spatially integrating these datasets with existing ground plot data 3. Constructing simulations and other statistical summaries and analyses that assess the effects of various plot and sample design combinations on inventory estimates and their precision, on remotely sensed image classification accuracy, and on overall inventory efficiency under different design scenarios that integrate remote sensing and ground plot data The goal of the project is to develop publications, workflows, and technical material that not only contributes to the science of resource monitoring, but also supports capacity building in partner countries. Required skills: A MSc or PhD (preferred, but not required) in a natural resource-related field, and: 1. Proficiency in GIS software (ArcGIS or similar) to view, manipulate and process both vector and raster data (examples include use of Python scripting for automation, map algebra calculations, tabular and zone-based summarization tools, use of projection methods for both raster and vector data, and basic cartographic skills) 2. Strong knowledge of graduate-level statistics (examples include the ability to generate calculations of estimates of population parameters from a dataset, generation of descriptive statistics, ability to summarize large datasets using automation tools and cross tabulations) 3. Practical knowledge of computer software (such as R, SAS, Microsoft Excel (with VBA for coding) or Python) including the ability to perform the operations listed in (2), in addition to batch processing 4. Proficiency in both written and spoken English. Desired skills: 1. Knowledge of sampling and forest inventory statistics 2. Knowledge of forestry 3. Knowledge of image classification principles and software (Erdas Imagine) Start date: As soon as the candidate is available Salary will depend on the education level and experience of the candidate. Please submit a copy of your resume or CV, a brief cover letter addressing your skills in relation to the above requirements, names and contact information of three references, and a photocopy of your latest graduate level university transcript. Contact info: Andrew Lister alis...@fs.fed.us 610.557.4038
